Clinical predictors of protracted length of stay in Ontario Complex Continuing Care hospitals.

BACKGROUND: Post-acute care hospitals are often subject to patient flow pressures because of their intermediary position along the continuum of care between acute care hospitals and community care or residential long-term care settings. The purpose of this study was to identify patient attributes associated with a prolonged length of stay in Complex Continuing Care hospitals. METHODS: Using information collected using the interRAI Resident Assessment Instrument Minimum Data Set 2.0 (MDS 2.0), a sample of 91,113 episodes of care for patients admitted to Complex Continuing Care hospitals between March 31, 2001 and March 31, 2013 was established. All patients in the sample were either discharged to a residential long-term care facility (e.g., nursing home) or to the community. Long-stay patients for each discharge destination were identified based on a length of stay in the 95th percentile. A series of multivariate logistic regression models predicting long-stay patient status for each discharge destination pathway were fit to characterize the association between demographic factors, residential history, health severity measures, and service utilization on prolonged length of stay in post-acute care. RESULTS: Risk factors for prolonged length of stay in the adjusted models included functional and cognitive impairment, greater pressure ulcer risk, paralysis, antibiotic resistant and HIV infection need for a feeding tube, dialysis, tracheostomy, ventilator or a respirator, and psychological therapy. Protective factors included advanced age, medical instability, a greater number of recent hospital and emergency department visits, cancer diagnosis, pneumonia, unsteady gait, a desire to return to the community, and a support person who is positive towards discharge. Aggressive behaviour was only a risk factor for patients discharged to residential long-term care facilities. Cancer diagnosis, antibiotic resistant and HIV infection, and pneumonia were only significant factors for patients discharged to the community. CONCLUSIONS: This study identified several patient attributes and process of care variables that are predictors of prolonged length of stay in post-acute care hospitals. This is valuable information for care planners and health system administrators working to improve patient flow in Complex Continuing Care and other post-acute care settings such as skilled nursing and inpatient rehabilitation facilities.

Updating the Cognitive Performance Scale.

This study presents the first update of the Cognitive Performance Scale (CPS) in 20 years. Its goals are 3-fold: extend category options; characterize how the new scale variant tracks with the Mini-Mental State Examination; and present a series of associative findings. Secondary analysis of data from 3733 older adults from 8 countries was completed. Examination of scale dimensions using older and new items was completed using a forward-entry stepwise regression. The revised scale was validated by examining the scale's distribution with a self-reported dementia diagnosis, functional problems, living status, and distress measures. Cognitive Performance Scale 2 extends the measurement metric from a range of 0 to 6 for the original CPS, to 0 to 8. Relating CPS2 to other measures of function, living status, and distress showed that changes in these external measures correspond with increased challenges in cognitive performance. Cognitive Performance Scale 2 enables repeated assessments, sensitive to detect changes particularly in early levels of cognitive decline.

Do SSRI Antidepressants Increase The Risk of Extrapyramidal Side Effects In Patients Taking Antipsychotics?

PURPOSE: Among antidepressants, selective serotonin reup-take inhibitors (SSRIs) have enjoyed great popularity among clinicians as well as generally wide acceptance and tolerance among patients. A potentially overlooked side effect of SSRIs is the occasional occurrence of extrapyramidal symptoms (EPS), which could be a concern when SSRIs are used with antipsychotics. This study was designed to explore the possible association between SSRI antidepressant use and the incidence of EPS side effects in patients who take concomitant antipsychotic medications. METHODS: The University of Michigan conducted a study at the four Michigan state mental health hospitals between May 2010 and October 2010. The Michigan Public Health Institute collected data using the InterRAI Mental Health Assessment (InterRAI MH). The present study is a retrospective cohort analysis of the cross-sectional data that were collected. Within these institutions, 693 residents were using antipsychotics. We measured the observed frequency of seven EPS recorded in the InterRAI MH within three groups of patients: 1) those on antipsychotic drugs who were taking an SSRI antidepressant; 2) those on antipsychotic drugs who were not taking an antidepressant; and 3) those on antipsychotic drugs who were taking a non-SSRI antidepressant. Differences in the prevalence of EPS were tested using one-way analysis of variance. RESULTS: There were no significant differences in the observed EPS frequencies among the three groups (F 2,18 = 0.01; P < 0.9901). CONCLUSION: In this study, SSRIs did not appear to potentiate the occurrence of EPS in patients using antipsychotics.

Derivation of a frailty index from the interRAI acute care instrument.

BACKGROUND: A better understanding of the health status of older inpatients could underpin the delivery of more individualised, appropriate health care. METHODS: 1418 patients aged ≥ 70 years admitted to 11 hospitals in Australia were evaluated at admission using the interRAI assessment system for Acute Care. This instrument surveys a large number of domains, including cognition, communication, mood and behaviour, activities of daily living, continence, nutrition, skin condition, falls, and medical diagnosis. RESULTS: Variables across multiple domains were selected as health deficits. Dichotomous data were coded as symptom absent (0 deficit) or present (1 deficit). Ordinal scales were recoded as 0, 0.5 or 1 deficit based on face validity and the distribution of data. Individual deficit scores were summed and divided by the total number considered (56) to yield a Frailty index (FI-AC) with theoretical range 0-1. The index was normally distributed, with a mean score of 0.32 (±0.14), interquartile range 0.22 to 0.41. The 99% limit to deficit accumulation was 0.69, below the theoretical maximum of 1.0. In logistic regression analysis including age, gender and FI-AC as covariates, each 0.1 increase in the FI-AC increased the likelihood of inpatient mortality twofold (OR: 2.05 [95% CI 1.70-2.48]). CONCLUSIONS: Quantification of frailty status at hospital admission can be incorporated into an existing assessment system, which serves other clinical and administrative purposes. This could optimise clinical utility and minimise costs. The variables used to derive the FI-AC are common to all interRAI instruments, and could be used to precisely measure frailty across the spectrum of health care.

Valproic Acid as a potentiator of metabolic syndrome in institutionalized residents on concomitant antipsychotics: fat chance, or slim to none?

BACKGROUND: Valproic acid (VPA) is one of the most commonly used antiepileptic medications worldwide; it is also a popular mood stabilizer for use in bipolar disorder and dementia. This study assessed whether VPA may potentiate metabolic side effects in patients with psychiatric disorders taking concomitant antipsychotics (APs). VPA alone has been associated with weight gain, dyslipidemia, hypertension, and diabetes. Patients with psychiatric disorders, especially those on second-generation (atypical) APs, appear to be at increased risk of these metabolic effects. A secondary purpose was to determine if a linear dose-response relationship exists between the VPA dose and adverse metabolic effects. METHODS: This cross-sectional study was conducted using data collected on all patients in the four state-operated psychiatric hospitals in Michigan using a comprehensive assessment instrument, the interRAI Mental Health. All patients taking both VPA and APs (n = 200) were compared to a control group of patients taking APs without VPA (n = 426). Patients were assessed for the presence of the following surrogate indicators of metabolic syndrome: weight gain; high body mass index (BMI greater than 30 kg/m(2)); very high BMI (BMI greater than 40 kg/m(2)); a diagnosis of diabetes mellitus; use of a prescribed statin medication; diagnosis of hyperlipidemia or dyslipidemia; hypertension; or the combination of any three of these factors: high BMI, hyperlipidemia or dyslipidemia, diabetes, and hypertension. Analysis also included assessment of the effect of VPA dosage on metabolic side effects. RESULTS: Patients in the VPA plus APs group were 3.2 kg heavier than those in the APs group (P = 0.05) at baseline. Compared with the APs group, the VPA plus APs group had a higher prevalence of high and very high BMI, diabetes, hypertension, and the combination of any three factors of high BMI, hyperlipidemia/dyslipidemia, diabetes, and hypertension. However, these differences were not statistically significant. Conversely, there was a slight but non-significant reduction in the prevalence of weight gain, prescribed statins, and hyperlipidemia/dyslipidemia in the VPA plus APs group than the APs group. Finally, higher doses of VPA were not found to be associated with a higher incidence of these metabolic side effects. CONCLUSION: Although the patients on VPA were slightly more than 3 kg heavier, VPA did not appear to be associated with significant metabolic effects in patients with psychiatric conditions taking typical and atypical APs. These metabolic effects also do not appear to be related to the dose of VPA.

Predicting risk of hospital and emergency department use for home care elderly persons through a secondary analysis of cross-national data.

BACKGROUND: Older adults remain the highest utilization group with unplanned visits to emergency departments and hospital admissions. Many have considered what leads to this high utilization and the answers provided have depended upon the independent measures available in the datasets used. This project was designed to further understanding of the reasons for older adult ED visits and admissions to acute care hospitals. METHODS: A secondary analysis of data from a cross-national sample of community residing elderly, 60 years of age or older, and most of whom received services from a local home-care program was conducted. The assessment instrument used in this study is the interRAI HC (home care), designed for use in assessing elderly home care recipients. The model specification stage of the study identified the baseline independent variables that do and do not predict the follow-up measure of hospitalization and ED use. Stepwise logistic regression was used next to identify characteristics that best identified elders who subsequently entered a hospital or visited an ED. The items generated from the final multivariate logistic equation using the interRAI home care measures comprise the interRAI Hospital-ED Risk Index. RESULTS: Independent measures in three key domains of clinical complications, disease diagnoses and specialized treatments were related to subsequent hospitalization or ED use. Among the eighteen clinical complication measures with higher, meaningful odds ratios are pneumonia, urinary tract infection, fever, chest pain, diarrhea, unintended weight loss, a variety of skin conditions, and subject self-reported poor health. Disease diagnoses with a meaningful relationship with hospital/ED use include coronary artery disease, congestive heart failure, cancer, emphysema and renal failure. Specialized treatments with the highest odds ratios were blood transfusion, IV infusion, wound treatment, radiation and dialysis. Two measures, Alzheimer's disease and day care appear to have a protective effect for hospitalization/ED use with lower odds ratios. CONCLUSIONS: Examination into "preventable" hospitalizations and re-hospitalizations for older adults who have the highest rates of utilization are occurring beneath an umbrella of assuring the highest quality of care and controlling costs. The interRAI Hospitalization-ED Risk Index offers an effective approach to predicting hospitalization utilization among community dwelling older adults.

Impact of cigarette smoking on utilization of nursing home services.

INTRODUCTION: Few studies have examined the effects of smoking on nursing home utilization, generally using poor data on smoking status. No previous study has distinguished utilization for recent from long-term quitters. METHODS: Using the Health and Retirement Study, we assessed nursing home utilization by never-smokers, long-term quitters (quit >3 years), recent quitters (quit ≤3 years), and current smokers. We used logistic regression to evaluate the likelihood of a nursing home admission. For those with an admission, we used negative binomial regression on the number of nursing home nights. Finally, we employed zero-inflated negative binomial regression to estimate nights for the full sample. RESULTS: Controlling for other variables, compared with never-smokers, long-term quitters have an odds ratio (OR) for nursing home admission of 1.18 (95% CI: 1.07-1.2), current smokers 1.39 (1.23-1.57), and recent quitters 1.55 (1.29-1.87). The probability of admission rises rapidly with age and is lower for African Americans and Hispanics, more affluent respondents, respondents with a spouse present in the home, and respondents with a living child. Given admission, smoking status is not associated with length of stay (LOS). LOS is longer for older respondents and women and shorter for more affluent respondents and those with spouses present. CONCLUSIONS: Compared with otherwise identical never-smokers, former and current smokers have a significantly increased risk of nursing home admission. That recent quitters are at greatest risk of admission is consistent with evidence that many stop smoking because they are sick, often due to smoking.

interRAI home care quality indicators.

BACKGROUND: This paper describe the development of interRAI's second-generation home care quality indicators (HC-QIs). They are derived from two of interRAI's widely used community assessments: the Community Health Assessment and the Home Care Assessment. In this work the form in which the quality problem is specified has been refined, the covariate structure updated, and two summary scales introduced. METHODS: Two data sets were used: at the client and home-care site levels. Client-level data were employed to identify HC-QI covariates. This sample consisted of 335,544 clients from Europe, Canada, and the United States. Program level analyses, where client level data were aggregated at the site level, were also based on the clients from the samples from Europe, Canada, and the United States. There were 1,654 program-based observations - 22% from Europe, 23% from the US, and 55% from Canada.The first task was to identify potential HC-QIs, including both change and prevalence measures. Next, they were reviewed by industry representatives and members of the interRAI network. A two-step process adjustment was followed to identify the most appropriate covariance structure for each HC-QI. Finally, a factor analytic strategy was used to identify HC-QIs that cluster together and thus are candidates for summary scales. RESULTS: The set of risk adjusted HC-QIs are multi-dimensional in scope, including measures of function, clinical complexity, social life, distress, and service use. Two factors were identified. The first includes a set of eleven measures that revolve around the absence of decline. This scale talks about functional independence and engagement. The second factor, anchored on nine functional improvement HC-QIs, referenced positively, this scale indicates a return to clinical balance. CONCLUSIONS: Twenty-three risk-adjusted, HC-QIs are described. Two new summary HC-QI scales, the "Independence Quality Scale" and the "Clinical Balance Quality Scale" are derived. In use at a site, these two scales can provide a macro view of local performance, offering a way for a home care agency to understand its performance. When scales perform less positively, the site then is able to review the HC-QI items that make up the scale, providing a roadmap for areas of greatest concern and in need of targeted interventions.

Scaling functional status within the interRAI suite of assessment instruments.

BACKGROUND: As one ages, physical, cognitive, and clinical problems accumulate and the pattern of loss follows a distinct progression. The first areas requiring outside support are the Instrumental Activities of Daily Living and over time there is a need for support in performing the Activities of Daily Living. Two new functional hierarchies are presented, an IADL hierarchical capacity scale and a combination scale integrating both IADL and ADL hierarchies. METHODS: A secondary analyses of data from a cross-national sample of community residing persons was conducted using 762,023 interRAI assessments. The development of the new IADL Hierarchy and a new IADL-ADL combined scale proceeded through a series of interrelated steps first examining individual IADL and ADL item scores among persons receiving home care and those living independently without services. A factor analysis demonstrated the overall continuity across the IADL-ADL continuum. Evidence of the validity of the scales was explored with associative analyses of factors such as a cross-country distributional analysis for persons in home care programs, a count of functional problems across the categories of the hierarchy, an assessment of the hours of informal and formal care received each week by persons in the different categories of the hierarchy, and finally, evaluation of the relationship between cognitive status and the hierarchical IADL-ADL assignments. RESULTS: Using items from interRAI's suite of assessment instruments, two new functional scales were developed, the interRAI IADL Hierarchy Scale and the interRAI IADL-ADL Functional Hierarchy Scale. The IADL Hierarchy Scale consisted of 5 items, meal preparation, housework, shopping, finances and medications. The interRAI IADL-ADL Functional Hierarchy Scale was created through an amalgamation of the ADL Hierarchy (developed previously) and IADL Hierarchy Scales. These scales cover the spectrum of IADL and ADL challenges faced by persons in the community. CONCLUSIONS: An integrated IADL and ADL functional assessment tool is valuable. The loss in these areas follows a general hierarchical pattern and with the interRAI IADL-ADL Functional Hierarchy Scale, this progression can be reliably and validly assessed. Used across settings within the health continuum, it allows for monitoring of individuals from relative independence through episodes of care.

Development of mental health quality indicators (MHQIs) for inpatient psychiatry based on the interRAI mental health assessment.

BACKGROUND: Outcome quality indicators are rarely used to evaluate mental health services because most jurisdictions lack clinical data systems to construct indicators in a meaningful way across mental health providers. As a result, important information about the effectiveness of health services remains unknown. This study examined the feasibility of developing mental health quality indicators (MHQIs) using the Resident Assessment Instrument - Mental Health (RAI-MH), a clinical assessment system mandated for use in Ontario, Canada as well as many other jurisdictions internationally. METHODS: Retrospective analyses were performed on two datasets containing RAI-MH assessments for 1,056 patients from 7 facilities and 34,788 patients from 70 facilities in Ontario, Canada. The RAI-MH was completed by clinical staff of each facility at admission and follow-up, typically at discharge. The RAI-MH includes a breadth of information on symptoms, functioning, socio-demographics, and service utilization. Potential MHQIs were derived by examining the empirical patterns of improvement and incidence in depressive symptoms and cognitive performance across facilities in both sets of data. A prevalence indicator was also constructed to compare restraint use. Logistic regression was used to evaluate risk adjustment of MHQIs using patient case-mix index scores derived from the RAI-MH System for Classification of Inpatient Psychiatry. RESULTS: Subscales from the RAI-MH, the Depression Severity Index (DSI) and Cognitive Performance Scale (CPS), were found to have good reliability and strong convergent validity. Unadjusted rates of five MHQIs based on the DSI, CPS, and restraints showed substantial variation among facilities in both sets of data. For instance, there was a 29.3% difference between the first and third quartile facility rates of improvement in cognitive performance. The case-mix index score was significantly related to MHQIs for cognitive performance and restraints but had a relatively small impact on adjusted rates/prevalence. CONCLUSIONS: The RAI-MH is a feasible assessment system for deriving MHQIs. Given the breadth of clinical content on the RAI-MH there is an opportunity to expand the number of MHQIs beyond indicators of depression, cognitive performance, and restraints. Further research is needed to improve risk adjustment of the MHQIs for their use in mental health services report card and benchmarking activities.

An evaluation of data quality in Canada's Continuing Care Reporting System (CCRS): secondary analyses of Ontario data submitted between 1996 and 2011.

BACKGROUND: Evidence informed decision making in health policy development and clinical practice depends on the availability of valid and reliable data. The introduction of interRAI assessment systems in many countries has provided valuable new information that can be used to support case mix based payment systems, quality monitoring, outcome measurement and care planning. The Continuing Care Reporting System (CCRS) managed by the Canadian Institute for Health Information has served as a data repository supporting national implementation of the Resident Assessment Instrument (RAI 2.0) in Canada for more than 15 years. The present paper aims to evaluate data quality for the CCRS using an approach that may be generalizable to comparable data holdings internationally. METHODS: Data from the RAI 2.0 implementation in Complex Continuing Care (CCC) hospitals/units and Long Term Care (LTC) homes in Ontario were analyzed using various statistical techniques that provide evidence for trends in validity, reliability, and population attributes. Time series comparisons included evaluations of scale reliability, patterns of associations between items and scales that provide evidence about convergent validity, and measures of changes in population characteristics over time. RESULTS: Data quality with respect to reliability, validity, completeness and freedom from logical coding errors was consistently high for the CCRS in both CCC and LTC settings. The addition of logic checks further improved data quality in both settings. The only notable change of concern was a substantial inflation in the percentage of long term care home residents qualifying for the Special Rehabilitation level of the Resource Utilization Groups (RUG-III) case mix system after the adoption of that system as part of the payment system for LTC. CONCLUSIONS: The CCRS provides a robust, high quality data source that may be used to inform policy, clinical practice and service delivery in Ontario. Only one area of concern was noted, and the statistical techniques employed here may be readily used to target organizations with data quality problems in that (or any other) area. There was also evidence that data quality was good in both CCC and LTC settings from the outset of implementation, meaning data may be used from the entire time series. The methods employed here may continue to be used to monitor data quality in this province over time and they provide a benchmark for comparisons with other jurisdictions implementing the RAI 2.0 in similar populations.

Beyond Section Q: prioritizing nursing home residents for transition to the community.

BACKGROUND: Nursing Facility Transition (NFT) programs often rely on self-reported preference for discharge to the community, as indicated in the Minimum Data Set (MDS) Section Q, to identify program participants. We examined other characteristics of long-stay residents discharged from nursing facilities by NFT programs, to "flag" similar individuals for outreach in the Money Follows the Person (MFP) initiative. METHODS: Three states identified persons who transitioned between 2001 and 2009 with the assistance of a NFT or MFP program. These were used to locate each participant's MDS 2.0 assessment just prior to discharge and to create a control sample of non-transitioned residents. Logistic regression and Automatic Interactions Detection were used to compare the two groups. RESULTS: Although there was considerable variation across states in transitionees' characteristics, a derived "Q + Index" was highly effective in identifying persons similar to those that states had previously transitioned. The Index displays high sensitivity (86.5%) and specificity (78.7%) and identifies 28.3% of all long-stayers for follow-up. The Index can be cross-walked to MDS 3.0 items. CONCLUSIONS: The Q + Index, applied to MDS 3.0 assessments, can identify a population closely resembling persons who have transitioned in the past. Given the US Government's mandate that states consider all transition requests and the limited staffing available at local contact agencies to address such referrals, this algorithm can also be used to prioritize among persons seeking assistance from local contact agencies and MFP providers.

A multi-stage process to develop quality indicators for community-based palliative care using interRAI data.

BACKGROUND: Individuals receiving palliative care (PC) are generally thought to prefer to receive care and die in their homes, yet little research has assessed the quality of home- and community-based PC. This project developed a set of valid and reliable quality indicators (QIs) that can be generated using data that are already gathered with interRAI assessments-an internationally validated set of tools commonly used in North America for home care clients. The QIs can serve as decision-support measures to assist providers and decision makers in delivering optimal care to individuals and their families. METHODS: The development efforts took part in multiple stages, between 2017-2021, including a workshop with clinicians and decision-makers working in PC, qualitative interviews with individuals receiving PC, families and decision makers and a modified Delphi panel, based on the RAND/ULCA appropriateness method. RESULTS: Based on the workshop results, and qualitative interviews, a set of 27 candidate QIs were defined. They capture issues such as caregiver burden, pain, breathlessness, falls, constipation, nausea/vomiting and loneliness. These QIs were further evaluated by clinicians/decision makers working in PC, through the modified Delphi panel, and five were removed from further consideration, resulting in 22 QIs. CONCLUSIONS: Through in-depth and multiple-stakeholder consultations we developed a set of QIs generated with data already collected with interRAI assessments. These indicators provide a feasible basis for quality benchmarking and improvement systems for care providers aiming to optimize PC to individuals and their families.

Using the RUG-III classification system for understanding the resource intensity of persons with intellectual disability residing in nursing homes.

Since 1991, the Minimum Data Set 2.0 (MDS 2.0) has been the mandated assessment in US nursing homes. The Resource Utilization Groups III (RUG-III) case-mix system provides person-specific means of allocating resources based on the variable costs of caring for persons with different needs. Retrospective analyses of data collected on a sample of 9707 nursing home residents (2.4% had an intellectual disability) were used to examine the fit of the RUG-III case-mix system for determining the cost of supporting persons with intellectual disability (intellectual disability). The RUG-III system explained 33.3% of the variance in age-weighted nursing time among persons with intellectual disability compared to 29.6% among other residents, making it a good fit among persons with intellectual disability in nursing homes. The RUG-III may also serve as the basis for the development of a classification system that describes the resource intensity of persons with intellectual disability in other settings that provide similar types of support.

The Forensic Supplement to the interRAI Mental Health Assessment Instrument: Evaluation and Validation of the Problem Behavior Scale.

Background: Numerous validation studies support the use of the interRAI Mental Health (MH) assessment system for inpatient mental health assessment, triage, treatment planning, and outcome measurement. However, there have been suggestions that the interRAI MH does not include sufficient content relevant to forensic mental health. We address this potential deficiency through the development of a Forensic Supplement (FS) to the interRAI MH system. Using three forensic risk assessment instruments (PCL-R; HCR-20; VRAG) that had a record of independent cross validation in the forensic literature, we identified forensic content domains that were missing in the interRAI MH. We then independently developed items to provide forensic coverage. The resulting FS is a single-page, 19-item supplementary document that can be scored along with the interRAI MH, adding approximately 10-15 min to administration time. We constructed the Problem Behavior Scale (PBS) using 11 items from the interRAI MH and FS. The Developmental Sample, 168 forensic mental health inpatients from two large mental health specialty hospitals, was assessed with both an earlier version of the interRAI MH and FS. This sample also provided us access to scores on the PCL-R, the HCR-20 and the VRAG. To validate our initial findings, we sought additional samples where scoring of the interRAI MH and the FS had been done. The first, the Forensic Sample (N = 587), consisted of forensic inpatients in other mental health units/hospitals. The second, the Correctional Sample (N = 618) was a random, representative sample of inmates in prisons, and the third, the Youth Sample (N = 90) comprised a group of youth in police custody. Results: The PBS ranged from 0 to 11, was positively skewed with most scores below 3, and had good internal consistency (Cronbach's Alpha = 0.80). In a test of concurrent validity, correlations between PBS scores and forensic risk scores were moderate to high (i.e., r with PCL-R Factor two of 0.317; with HCR-20 Clinical of 0.46; and with HCR-20 Risk of 0.39). In a test of convergent validity, we used Binary Logistic Regression to demonstrate that the PBS was related to three negative patient experiences (recent verbal abuse, use of a seclusion room, and failure to attain an unaccompanied leave). For each of these three samples, we conducted the same convergent validity statistical analyses as we had for the Developmental Sample and the earlier findings were replicated. Finally, we examined the relationship between PBS scores and care planning triggers, part of the interRAI systems Clinical Assessment Protocols (CAPs). In all three validity samples, the PBS was significantly related to the following CAPs being triggered: Harm to Others, Interpersonal Conflict, Traumatic Life Events, and Control Interventions. These additional validations generalize our findings across age groups (adult, youth) and across health care and correctional settings. Conclusions: The FS improves the interRAI MH's ability to identify risk for negative patient experiences and assess clinical needs in hospitalized/incarcerated forensic patients. These results generalize across age groups and across health care and correctional settings.

Adjustment of nursing home quality indicators.

BACKGROUND: This manuscript describes a method for adjustment of nursing home quality indicators (QIs) defined using the Center for Medicaid & Medicare Services (CMS) nursing home resident assessment system, the Minimum Data Set (MDS). QIs are intended to characterize quality of care delivered in a facility. Threats to the validity of the measurement of presumed quality of care include baseline resident health and functional status, pattern of comorbidities, and facility case mix. The goal of obtaining a valid facility-level estimate of true quality of care should include adjustment for resident- and facility-level sources of variability. METHODS: We present a practical and efficient method to achieve risk adjustment using restriction and indirect and direct standardization. We present information on validity by comparing QIs estimated with the new algorithm to one currently used by CMS. RESULTS: More than half of the new QIs achieved a "Moderate" validation level. CONCLUSIONS: Given the comprehensive approach and the positive findings to date, research using the new quality indicators is warranted to provide further evidence of their validity and utility and to encourage their use in quality improvement activities.

A Case-Mix System for Children and Youth With Developmental Disabilities.

Limited funding across health and social service programs presents a challenge regarding how to best match resources to the needs of the population. There is increasing consensus that differences in individual characteristics and care needs should be reflected in variations in service costs, which has led to the development of case-mix systems. The present study sought to develop a new approach to allocate resources among children and youth with intellectual and developmental disabilities (IDD) as part of a system-wide Medicaid payment reform initiative in Arkansas. To develop the system, assessment data collected using the interRAI Child and Youth Mental Health-Developmental Disability instrument was matched to paid service claims. The sample consisted of 346 children and youth with developmental disabilities in the home setting. Using automatic interactions detection, individuals were sorted into unique, clinically relevant groups (ie, based on similar resource use) and a standardized relative measure of the cost of services provided to each group was calculated. The resulting case-mix system has 8 distinct, final groups and explains 30% of the variance in per diem costs. Our analyses indicate that this case-mix classification system could provide the foundation for a future prospective payment system that is centered around stability and equitability in the allocation of limited resources within this vulnerable population.

Sharing clinical information across care settings: the birth of an integrated assessment system.

BACKGROUND: Population ageing, the emergence of chronic illness, and the shift away from institutional care challenge conventional approaches to assessment systems which traditionally are problem and setting specific. METHODS: From 2002, the interRAI research collaborative undertook development of a suite of assessment tools to support assessment and care planning of persons with chronic illness, frailty, disability, or mental health problems across care settings. The suite constitutes an early example of a "third generation" assessment system. RESULTS: The rationale and development strategy for the suite is described, together with a description of potential applications. To date, ten instruments comprise the suite, each comprising "core" items shared among the majority of instruments and "optional" items that are specific to particular care settings or situations. CONCLUSION: This comprehensive suite offers the opportunity for integrated multi-domain assessment, enabling electronic clinical records, data transfer, ease of interpretation and streamlined training.

A Case-Mix System for Adults with Developmental Disabilities.

Effective management of publicly funded services matches the provision of needed services with cost-efficient payment methods. Payment systems that recognize differences in care needs (eg, case-mix systems) allow for greater proportions of available funds to be directed to providers supporting individuals with more needs. We describe a new way to allocate funds spent on adults with intellectual disabilities (ID) as part of a system-wide Medicaid payment reform initiative in Arkansas. Analyses were based on population-level data for persons living at home, collected using the interRAI ID assessment system, which were linked to paid service claims. We used automatic interactions detection to sort individuals into unique groups and provide a standardized relative measure of the cost of the services provided to each group. The final case-mix system has 33 distinct final groups and explains 26% of the variance in costs, which is similar to other systems in health and social services sectors. The results indicate that this system could be the foundation for a future case-mix approach to reimbursement and stand the test of "fairness" when examined by stakeholders, including parents, advocates, providers, and political entities.

The interRAI Suite of Mental Health Assessment Instruments: An Integrated System for the Continuum of Care.

The lives of persons living with mental illness are affected by psychological, biological, social, economic, and environmental factors over the life course. It is therefore unlikely that simple preventive strategies, clinical treatments, therapeutic interventions, or policy options will succeed as singular solutions for the challenges of mental illness. Persons living with mental illness receive services and supports in multiple settings across the health care continuum that are often fragmented, uncoordinated, and inadequately responsive. Appropriate assessment is an important tool that health systems must deploy to respond to the strengths, preferences, and needs of persons with mental illness. However, standard approaches are often focused on measurement of psychiatric symptoms without taking a broader perspective to address issues like growth, development, and aging; physical health and disability; social relationships; economic resources; housing; substance use; involvement with criminal justice; stigma; and recovery. Using conglomerations of instruments to cover more domains is impractical, inconsistent, and incomplete while posing considerable assessment burden. interRAI mental health instruments were developed by a network of over 100 researchers, clinicians, and policy experts from over 35 nations. This includes assessment systems for adults in inpatient psychiatry, community mental health, emergency departments, mobile crisis teams, and long-term care settings, as well as a screening system for police officers. A similar set of instruments is available for child/youth mental health. The instruments form an integrated mental health information system because they share a common assessment language, conceptual basis, clinical emphasis, data collection approach, data elements, and care planning protocols. The key applications of these instruments include care planning, outcome measurement, quality improvement, and resource allocation. The composition of these instruments and psychometric properties are reviewed, and examples related to homeless are used to illustrate the various applications of these assessment systems.